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memorydetective

Single-call cross-schema summary card for a .trace bundle

summarizeTrace

Chains multiple analyzers to return a structured summary and a compact markdown card from a .trace file, highlighting the biggest user-impact finding.

Instructions

[mg.synthesize] The trace-to-summary-card-in-one-call play. Chains inspectTrace + the matching analyze* tools (potential-hangs, animation-hitches, time-profile, allocations, app-launch) and returns BOTH a structured per-area result AND a pre-rendered compact markdown card (< 10 KB at default settings). Use this as the FIRST call when handed a .trace if you want one synthesis pass instead of chaining 5-6 analyzers manually. The markdown card carries a 1-sentence headline naming the biggest user-impact finding, then per-area sub-sections, then suggestedNextCalls[] for drilling in. Empty schemas are suppressed from the card to reduce noise. Failed analyzers (e.g. xctrace SIGSEGV on time-profile) surface inline with their workaround notice. Pass verbose: true to expand each section's top-N from 5 to 15+. Pass focus: "hangs" | "hitches" | "allocations" | "launch" to bias the summary toward a specific area.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tracePathYesAbsolute path to a `.trace` bundle (output of `xcrun xctrace record` or Instruments).
focusNoWhen set to a specific area, the summary card emphasizes that area and downplays others. Useful for piping into more focused agent loops. Default `all`.all
verboseNoWhen true, the markdown card includes the full top-N per area (15+ rows per section) instead of the default 5. Trade-off: card grows from <10 KB to potentially 30+ KB.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must disclose behavior fully. It explains chaining of tools, output composition (structured result + markdown card), handling of empty schemas and analyzer failures, and the impact of verbose/focus parameters. It does not discuss performance or authorization, but covers key behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact yet comprehensive, starting with a concise summary and then detailing usage, output, and parameter effects. Every sentence adds value, though it could be slightly more concise without losing information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (chaining multiple analyzers), the absence of annotations and output schema, the description is remarkably complete. It explains the output format (headline, per-area sections, suggestedNextCalls), parameter effects, and edge cases (analyzer failures), fully compensating for missing metadata.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% (all three parameters have descriptions). The description adds value by clarifying tracePath ('absolute path'), focus ('emphasizes that area'), and verbose ('card size trade-off'), going beyond the schema's basic descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb 'summarize' and resource '.trace bundle', and clearly distinguishes from siblings by describing it as a single-call synthesis that chains multiple analyzers, contrasting with individual analyzer tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises using as the first call for a synthesis pass instead of manually chaining analyzers, and describes parameter effects. However, it could more explicitly state when not to use it (e.g., for raw data from a specific analyzer).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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